Personalized content recommendation system with improved attention ability

Abstract

The invention discloses a personalized content recommendation system with improved attention ability. The personalized content recommendation system comprises a user login module, an evaluation module, a content pushing module, an ability training module and a result feedback module. According to the method, analysis dimensions are increased, a student ability semantic dictionary is constructed, attention quality dimensions and cognitive ability dimensions are combined, relevant feature semantics such as human body temperament types and learning styles are fused, and an effective attention ability analysis model and an effective learner feature model are constructed. Attention is taken as a main line, and an attention ability improvement closed loop of initial evaluation, initial content pushing, ability training, staged development evaluation, result feedback, training, evaluation... is provided for a user; training content and a multi-mode guide mode are displayed to the user, and the attention ability improvement training content is comprehensively integrated into a system. Meanwhile, the system corrects and adjusts the training content of the user according to the user evaluation result, and the attention ability training level is further improved.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a personalized content recommendation system for improving attention ability. Background technique [0002] At present, the existing attention ability improvement system mainly has the following two problems: 1. Lack of attention ability analysis model support, the existing attention ability training system only focuses on the stability of attention, the breadth of attention, the distribution of attention and the transfer of attention The initial analysis dimension is established in four aspects, the analysis dimension is few, and the semantic lexicon is lacking, so it is impossible to establish an effective personal ability model; 2. After the existing attention ability training system gives a simple attention ability analysis, because there is no effective Analyzing the model, the "personalized" training program given is simply to divide the users into grades, and then pus...

AI Technical Summary

Problems solved by technology

[0002] At present, the existing attention ability improvement system mainly has the following two problems: 1. Lack of attention ability analysis model support, the existing attention ability training system only focuses on the stability of attention, the breadth of attention, the distribution of attention and the transfer of attention The initial analysis dimension is established in four aspects, the analysis dimension is few, and the semantic lexicon is lacking, so it is impossible to establish an effective personal ability model; 2. After the existing attention ability training system gives a simple attention ability analysis, because there is no effective Analyzing the model, the "personalized" training plan given is simply to divide the users into grades, and push the corresponding grades of course content to 4-5 user grade groups

This kind of attention ability improvement system cannot push targeted personalized content to users, and cannot effectively solve the problem of user attention ability improvement, and the overall effect is not good.

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